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About myself

• PhD student in Bioinformatics under Dr. Amrit Singh supervision

• BSc. in Math + minor in Data Science

• What does “bioinformatician” do?

  • Assist researchers like you to better understand what you’re data means
  • We’re just coders that know little bit more bio …

• Currently working in creating pipeline, tools, models analyzing biological data in an automated-fashion

  • Focused on machine learning & AI
  • Reproducible workflows

Single Cell RNA-seq

What is single cell RNA sequencing?

Loading data

The data is from a study (Kang et al. 2018) and publicly avaliable through R’s ExperimentHub function

eh <- ExperimentHub() #  Initialize the hub as some list object
sce <- eh[["EH2259"]] # We could then extract the match entry by taking this entry from out hub
# Then print it
sce

class: SingleCellExperiment 
dim: 35635 29065 
metadata(0):
assays(1): counts
rownames(35635): MIR1302-10 FAM138A ... MT-ND6 MT-CYB
rowData names(2): ENSEMBL SYMBOL
colnames(29065): AAACATACAATGCC-1 AAACATACATTTCC-1 ... TTTGCATGGTTTGG-1
  TTTGCATGTCTTAC-1
colData names(5): ind stim cluster cell multiplets
reducedDimNames(1): TSNE
mainExpName: NULL
altExpNames(0):

• After loaded data should inspect basic information
• What are rows? column? size of data?
• Rows = genes
• Columns = cells

Preprocessing of data before analysis

The data retrieved is rawest form, not all of it is useful.

Caveats:

Remove undetected genes

counts(sce) |> colnames() |> sample(10)

 [1] "GAAGTAGACTGTAG-1" "ATAAGTTGGTGCTA-1" "GGTACATGCTATGG-1" "GAGTCTGATTCGGA-1"
 [5] "AACAGCACTCTTTG-1" "TCCCGATGCCCTTG-1" "ACTCCTCTTAGAAG-1" "GTCCCATGTCAAGC-1"
 [9] "ACGTAGACCAGTCA-1" "TGGTATCTCACTAG-1"